A functional assay-based procedure to classify mismatch repair gene variants in Lynch syndrome

Abstract

Purpose: To enhance classification of variants of uncertain significance (VUS) in the DNA mismatch repair (MMR) genes in the cancer predisposition Lynch syndrome, we developed the cell-free in vitro MMR activity (CIMRA) assay. Here, we calibrate and validate the assay, enabling its integration with in silico and clinical data.

Methods: Two sets of previously classified MLH1 and MSH2 variants were selected from a curated MMR gene database, and their biochemical activity determined by the CIMRA assay. The assay was calibrated by regression analysis followed by symmetric cross-validation and Bayesian integration with in silico predictions of pathogenicity. CIMRA assay reproducibility was assessed in four laboratories.

Results: Concordance between the training runs met our prespecified validation criterion. The CIMRA assay alone correctly classified 65% of variants, with only 3% discordant classification. Bayesian integration with in silico predictions of pathogenicity increased the proportion of correctly classified variants to 87%, without changing the discordance rate. Interlaboratory results were highly reproducible.

Conclusion: The CIMRA assay accurately predicts pathogenic and benign MMR gene variants. Quantitative combination of assay results with in silico analysis correctly classified the majority of variants. Using this calibration, CIMRA assay results can be integrated into the diagnostic algorithm for MMR gene variants.

Keywords: Lynch syndrome; assay calibration; functional assay; variant classification; variants of uncertain significance.

Fig. 1. Outline of the cell-free in vitro MMR activity (CIMRA) assay and of this study.

(a) Outline of the CIMRA assay. The figure describes testing of an MSH2 variant but testing MLH1 variants is technically similar. (b) Flow diagram for major steps of the study design. The variants in the “CIMRA Assays set 1 and 2” boxes are coloured according to their InSiGHT classification, see also Fig. 2. PCR polymerase chain reaction, ROC receiver operating characteristic, WT wild type.

Fig. 2. Calibration and validation of the CIMRA assay.

(a) Relative repair efficiencies for MLH1 and MSH2 variants from the first CIMRA training set. Variants are colored according to their InSiGHT classification (see legend in figure). The MSH2 p.A636P variant and the MLH1 p.G67R variant are included in every experiment as repair-deficient (pathogenic) controls. Bars represent mean ± SEM of 3–5 experiments. Asterisks indicate variants whose MMR activity appears discordant with their original InSiGHT classification. (b) Receiver operator characteristic (ROC) curve for the first CIMRA assay training. (c) Regressions of first (blue) and second (red) CIMRA assay training values against odds in favor of pathogenicity. Both curves are embedded in their 80% confidence envelopes. Note that the y-axes in (c) and (f) display probability of pathogenicity rather than Log(odds in favor of pathogenicity), to emphasize sigmoid calibration bounded at probabilities of 1.00 and 0.00. (d) As in (a), but for second CIMRA assay training. (e) ROC curve for the second CIMRA assay training. (f) As in (c), but shown here is the final calibration curve combining first CIMRA assay training (n = 35) and second CIMRA assay training (n = 35) substitutions; the regression curve is embedded in both 80% and 95% confidence envelopes. IARC International Agency for Research on Cancer.

Fig. 3. A Bayesian integration of cell-free in vitro MMR activity (CIMRA) assay values and in silico predictions of pathogenicity correctly classifies ~90% of missense variants.

(a) Receiver operating characteristic (ROC) curve of a cross-validation between the two CIMRA training runs. (b) ROC curve of a two-component (CIMRA assay + in silico) analysis. (c) Distribution of probabilities of pathogenicity for 68 missense variants as estimated by in silico analysis only (top), CIMRA only (middle), or integrated two-component analysis (CIMRA plus the computational Prior-P; bottom). The gray, dotted, lines highlight probabilities of 0.05 and 0.95. #: Because the probabilities of pathogenicity estimated by the computational Prior-P are capped at 0.1 and 0.9, the bins <0.08 and >0.92 are empty. (d) Subcellular localization of wild-type (WT) and mutant MLH1 protein. NIH3T3 cells were transiently transfected with pYFP-MLH1 WT (shown in red, left panel) together with pCFP-MLH1 (WT or mutant; shown in green, middle panel). The localization of the fusion proteins were analyzed using confocal laser scanning microscopy. The corresponding outline of cells in Nomarski contrast are shown (right panel) where the yellow color indicates overlay of the two proteins. IARC International Agency for Research on Cancer.

Fig. 4. Multilaboratory assessment of cell-free in vitro MMR activity (CIMRA) assay reproducibility.

(a) MSH2 variants and controls were tested for CIMRA assay activity in different centers worldwide (see legends in figure). The MSH2 p.A636P variant is included in every experiment as a repair-deficient control. Bars represent mean ± SEM of 3–4 experiments. Numbers below the diagrams indicate the IARC classification. * Variant discordantly classified, # variant unclassified. (b) As with (a), but for MLH1 variants, where MLH1 p.G67R is the experimental control. IARC International Agency for Research on Cancer, LUMC Leiden University Medical Center, QIMR QIMR Berghofer Medical Research Institute, UMCG University Medical Center Groningen, WT wild type.